Are you wasting your time to Learn "Python For Data Science"?

Reason Why you are not getting into job as a Data Scientist?

It's simple, Only Learning is not the key to land your job as a Data Scientist,Experience with Learning make your ML model more fit & chance to crack the interview(When you start learning any course,you won't apply it practically & that is where we start wrong way of learning i.e. without experience instead what things you have learned just try those while working with Data Set & what thing you need to learn to apply "Learn at the same time" & apply,believe me you will enhance your way of learning & able to explain stuff by your own way).

Data Science is more of your passion,curiosity & importantly research with patience.You can work with best way of learning while looking out with some existing project,understand the required problem statement & 'learn to analyze the code at first',work out with at least 5 project & then take any different problem statement 'you can analyze progress of learning with experience'.

Many of the you wasting your time to learn python ,visualization libraries like pandas,numpy etc,. & start searching for job or internship in Data Science Domain which is a Myth because you won't get it for sure.You just have to know what & where you have to use such skills as a Data Scientist & .instead focus on core python which can help you in many ways(Remember::Analyzing code is difficult as compare to writing a code,understand the concept & practice as much as you can with different problem statement).

Whether you believe or not but no one is perfect in coding difference is that,they know what graph they have to plot & search for the same over google then implementing the same.

We should thanks bamboolib.com to make our work more easier which can save our up-to 12 hour while solving any particular problem statement.

What is Bamboolib?

Bamboolib is a python package for easy data exploration & transformation with pandas. You can use it with Jupyter Notebook or JupyterLab. ... All transformations come with full keyboard control, making bamboolib the first GUI loved both by pandas-savvy users as well as Python novices.

Why do we need such tools?

You know the answer very well,when you want to plot any graph with one parameter or with different column names,you always search the code & implementing(around 90% of them do the same) which is not wrong & we waste around 12 to 15 hour ,with bamboolib we can save the time & work out with more better insights to proceed with.

You may have a question,that now getting job will be easy?

No,it won't as anyone can use the tool & plot the graph but as a Data Scientist you should think first,research according to your problem statement then only you can make best use of such tools which can be the tools for those who love Research & Statistics.

Even high school student know statistics(mean,mode,median & standard deviation etc) but what difference you can make with statistics as a Data Scientist.

Crazy part is when you have been asked how you will use mean,mode & median?

What you will answer is "Formula" but think once what will be difference between you & high school student then.:)

Let's start how you can use bamboolib with kaggle step by step implementation(Even you can work with jupyter lab & jupyter notebook):

First step,do open kaggle kernel & on the right upper you can find an option to enable internet as shown in below figure::

Then do use above code shown in image to import bamboolib with kaggle kernel & run it.

After successful run of particular code shown in above image,do refresh the page & wait for some seconds.

After refresh,do use above code shown in image to import data set successfully.

Then do call your data frame that you have initialized as shown above.

After particular code run successfully you can see the option "bamboolib UI",do click & you can see the above image as shown.

As we can see "Sex" column which have two unique values i.e. female & male ,in python if we have to convert this column in two columns or one columns with respect to 0 & 1 where 0 will represent female & 1 will represent male.

just search 'one hot encoding' in search transformation bar & when you click ,on the right side table will be pop as shown & choose your column where you have to apply one hot encoding as shown in below figure.

As shown in above image when you select particular column name you can see two option,where first option will convert female to 0 & male to 1 & another option 'create dummy for missing values' will divide sex column in two parts with male & female.

It's up-to you how you have to take it,here we have choose first option

Let's see what change we can see after as shown in below image

If you want to change column name just double click on particular column 'sex' changed to 0 for female & 1 for male.You can also change name of the column as well 'sex' to "Gender".

You just have to double click on'sex' column & another small window will pop up at right as shown in figure.

Change the name,click on rename you will see the result & in summary part you can see all unique values with percentage of missing values ,so that you can work accordingly further to handle missing values.

Column name changed successfully as you can see in below image & changed to 0 & 1.

As you can see another column "birth_year" & we have to change it into 'age',how let' s see simple code dx["Age"] = 2020 - dx["birth_year],to implement this search 'New Column Formula' in search transformation column as shown below "bamboolib UI option'.

As you can see below image type the formula & click on execute.

Then we can see the changes in below image where new column created "Age"(you have to scroll the screen till last,as all new column will append by default & you have to delete column 'birth_year' now.

As we have seen some of the Data Cleaning part using bamboolib & trust we have come through only 2% of part,you can do much more things,so what you are waiting for.

Give it a try!!

Now ,as shown in below image do click on 'Explore DataFrame' & you can observe we can plot almost all different types of visualization with great Info from the Data Set.

As seen in below image after you click on 'Explore DataFrame',Where 'Glimpse' will give you overview of Data Set for each column ,'Columns' will show you all the parameters present in given Data Set,'Predictor patterns' will show you the relation of all parameters &'Correlation Matrix' will show you which parameter is strongly correlated or not,so that you can make use of such information to proceed further.

If you click on 'create plot' below screen will pop up where you can select type of plot you want to see & between which parameters.As seen in figure we have select 'Histogram' & 'infection_reason' & you can also plot graph between two variables while adding another parameter name in 'Add property' vice versa.

Asap you select,you can see the below output within some seconds,where you can analyze that there are more number of 'NAN' values present & you have to figure out how you will deal with 'Null' values.

You can work with more stuff with bamboolib,it's just an basics we have gone through.

As shown in below figure we are plotting histogram with another column name.

Below is the output you can see in below image.

So,what you are waiting for.

Are you going to start your career but to be very frank do not waste your money to the expensive courses before knowing whether Data Science is your cup of tea or not.

Do connect with me & schedule your free meeting to start your career as a Data Scientist(do drop a mail to [email protected]).